test/test_statistics.rb in statsample-0.5.1 vs test/test_statistics.rb in statsample-0.6.0
- old
+ new
@@ -9,74 +9,85 @@
def test_recode_repeated
a=%w{a b c c d d d e}
exp=["a","b","c_1","c_2","d_1","d_2","d_3","e"]
assert_equal(exp,a.recode_repeated)
end
- def test_is_number
- assert("10".is_number?)
- assert("-10".is_number?)
- assert("0.1".is_number?)
- assert("-0.1".is_number?)
- assert("10e3".is_number?)
- assert("10e-3".is_number?)
- assert(!"1212-1212-1".is_number?)
- assert(!"a10".is_number?)
- assert(!"".is_number?)
-
+ def test_is_number
+ assert("10".is_number?)
+ assert("-10".is_number?)
+ assert("0.1".is_number?)
+ assert("-0.1".is_number?)
+ assert("10e3".is_number?)
+ assert("10e-3".is_number?)
+ assert(!"1212-1212-1".is_number?)
+ assert(!"a10".is_number?)
+ assert(!"".is_number?)
+
+ end
+ def test_chi_square
+ assert_raise TypeError do
+ Statsample::Test.chi_square(1,1)
end
- def test_chi_square
- assert_raise TypeError do
- Statsample::Test.chi_square(1,1)
- end
- real=Matrix[[95,95],[45,155]]
- expected=Matrix[[68,122],[72,128]]
- assert_nothing_raised do
- chi=Statsample::Test.chi_square(real,expected)
- end
+ real=Matrix[[95,95],[45,155]]
+ expected=Matrix[[68,122],[72,128]]
+ assert_nothing_raised do
chi=Statsample::Test.chi_square(real,expected)
- assert_in_delta(32.53,chi,0.1)
end
+ chi=Statsample::Test.chi_square(real,expected)
+ assert_in_delta(32.53,chi,0.1)
+ end
- def test_estimation_mean
- v=([42]*23+[41]*4+[36]*1+[32]*1+[29]*1+[27]*2+[23]*1+[19]*1+[16]*2+[15]*2+[14,11,10,9,7]+ [6]*3+[5]*2+[4,3]).to_vector(:scale)
- assert_equal(50,v.size)
- assert_equal(1471,v.sum())
- limits=Statsample::SRS.mean_confidence_interval_z(v.mean(), v.sds(), v.size,676,0.80)
+ def test_estimation_mean
+ v=([42]*23+[41]*4+[36]*1+[32]*1+[29]*1+[27]*2+[23]*1+[19]*1+[16]*2+[15]*2+[14,11,10,9,7]+ [6]*3+[5]*2+[4,3]).to_vector(:scale)
+ assert_equal(50,v.size)
+ assert_equal(1471,v.sum())
+ limits=Statsample::SRS.mean_confidence_interval_z(v.mean(), v.sds(), v.size,676,0.80)
+ end
+ def test_estimation_proportion
+ # total
+ pop=3042
+ sam=200
+ prop=0.19
+ assert_in_delta(81.8, Statsample::SRS.proportion_total_sd_ep_wor(prop, sam, pop), 0.1)
+
+ # confidence limits
+ pop=500
+ sam=100
+ prop=0.37
+ a=0.95
+ l= Statsample::SRS.proportion_confidence_interval_z(prop, sam, pop, a)
+ assert_in_delta(0.28,l[0],0.01)
+ assert_in_delta(0.46,l[1],0.01)
+ end
+ def test_ml
+ if(true)
+ real=[1,1,1,1].to_vector(:scale)
+
+ pred=[0.0001,0.0001,0.0001,0.0001].to_vector(:scale)
+ # puts Statsample::Bivariate.maximum_likehood_dichotomic(pred,real)
+
end
- def test_estimation_proportion
- # total
- pop=3042
- sam=200
- prop=0.19
- assert_in_delta(81.8, Statsample::SRS.proportion_total_sd_ep_wor(prop, sam, pop), 0.1)
-
- # confidence limits
- pop=500
- sam=100
- prop=0.37
- a=0.95
- l= Statsample::SRS.proportion_confidence_interval_z(prop, sam, pop, a)
- assert_in_delta(0.28,l[0],0.01)
- assert_in_delta(0.46,l[1],0.01)
- end
- def test_ml
- if(true)
- real=[1,1,1,1].to_vector(:scale)
-
- pred=[0.0001,0.0001,0.0001,0.0001].to_vector(:scale)
- # puts Statsample::Bivariate.maximum_likehood_dichotomic(pred,real)
-
- end
- end
- def test_simple_linear_regression
- a=[1,2,3,4,5,6].to_vector(:scale)
- b=[6,2,4,10,12,8].to_vector(:scale)
- reg = Statsample::Regression::Simple.new_from_vectors(a,b)
- assert_in_delta((reg.ssr+reg.sse).to_f,reg.sst,0.001)
- assert_in_delta(Statsample::Bivariate.pearson(a,b),reg.r,0.001)
- assert_in_delta(2.4,reg.a,0.01)
- assert_in_delta(1.314,reg.b,0.001)
- assert_in_delta(0.657,reg.r,0.001)
- assert_in_delta(0.432,reg.r2,0.001)
-
- end
+ end
+ def test_simple_linear_regression
+ a=[1,2,3,4,5,6].to_vector(:scale)
+ b=[6,2,4,10,12,8].to_vector(:scale)
+ reg = Statsample::Regression::Simple.new_from_vectors(a,b)
+ assert_in_delta((reg.ssr+reg.sse).to_f,reg.sst,0.001)
+ assert_in_delta(Statsample::Bivariate.pearson(a,b),reg.r,0.001)
+ assert_in_delta(2.4,reg.a,0.01)
+ assert_in_delta(1.314,reg.b,0.001)
+ assert_in_delta(0.657,reg.r,0.001)
+ assert_in_delta(0.432,reg.r2,0.001)
+ end
+ def test_u_mannwhitney
+ a=[1,2,3,4,5,6].to_scale
+ b=[0,5,7,9,10,11].to_scale
+ assert_equal(7.5, Statsample::Test.u_mannwhitney(a,b).u)
+ assert_equal(7.5, Statsample::Test.u_mannwhitney(b,a).u)
+ a=[1, 7,8,9,10,11].to_scale
+ b=[2,3,4,5,6,12].to_scale
+ assert_equal(11, Statsample::Test.u_mannwhitney(a,b).u)
+
+
+
+ end
end